JP2023003303A - Processing device, motorcycle, and processing method - Google Patents

Abstract

To provide a processing device which is mounted on a motorcycle and can reduce the cost of the motorcycle capable of determining the wetting of a road surface.SOLUTION: A processing device according to the present invention is mounted on a motorcycle. The processing device includes: an acquisition section for acquiring the traveling characteristic of the motorcycle on the basis of an output from an inertial measurement sensor used for the control of the behavior of the motorcycle; and a determination section for comparing the traveling characteristic acquired by the acquisition section and reference data to determine the wetting of a road surface.SELECTED DRAWING: Figure 2

Description

The present invention relates to a processing device mounted on a motorcycle, a motorcycle equipped with the processing device, and a processing method used for the motorcycle.

The behavior of a motorcycle while running is more susceptible to the effects of the road surface than that of a four-wheeled vehicle. Therefore, information on whether the road surface is wet or not is very useful for motorcycles. Therefore, a conventional motorcycle has been proposed that includes a raindrop sensor that directly detects rain and determines whether the road surface is wet based on the output of the raindrop sensor (see, for example, Patent Document 1).

JP 2018-118569 A

Conventional motorcycles have had to be equipped with raindrop sensors that directly detect rain in order to determine whether the road surface is wet. Therefore, there is a problem that conventional motorcycles that can determine whether the road surface is wet are expensive.

SUMMARY OF THE INVENTION It is an object of the present invention to provide a processing device mounted on a motorcycle and capable of determining the wetness of the road surface and reducing the cost of the motorcycle. With the goal. Another object of the present invention is to provide a motorcycle equipped with such a processing device. Another object of the present invention is to provide a processing method used in a motorcycle, which is capable of determining the wetness of the road surface and reducing the cost of the motorcycle.

A processing device according to the present invention is a processing device mounted on a motorcycle, and is an acquisition unit that acquires the running characteristics of the motorcycle based on the output of an inertial measurement sensor used to control the behavior of the motorcycle. and a determination unit that compares the driving characteristics acquired by the acquisition unit with reference data and determines wetness of the road surface.

A motorcycle according to the present invention also includes a processing device according to the present invention.

In addition, a processing method according to the present invention is a processing method used in a motorcycle, which acquires the running characteristics of the motorcycle based on the output of an inertial measurement sensor used to control the behavior of the motorcycle. and a determining step of comparing the driving characteristics acquired in the acquiring step with reference data to determine wetness of the road surface.

A motorcycle whose behavior is controlled includes an inertial measurement sensor, and behavior is controlled based on the output of the inertial measurement sensor. Here, the present invention can determine wetness of the road surface based on the output of the inertial measurement sensor used to control the behavior of the motorcycle. Therefore, by applying the present invention to a motorcycle whose behavior is controlled, it is possible to reduce the cost of a motorcycle that can determine whether the road surface is wet.

1 is a side view of a motorcycle according to an embodiment of the invention; FIG. 1 is a block diagram showing a processing device according to an embodiment of the invention; FIG. It is a figure for demonstrating an example of the determination method of the wetness of the road surface which the determination part of the processing apparatus which concerns on embodiment of this invention performs. It is a figure for demonstrating an example of the determination method of the wetness of the road surface which the determination part of the processing apparatus which concerns on embodiment of this invention performs. FIG. 5 is a diagram for explaining a suitable time period when the determining unit of the processing device according to the embodiment of the present invention determines whether the road surface is wet; It is a figure which shows the control flow of an example of operation|movement of the processing apparatus which concerns on embodiment of this invention. It is a block diagram which shows the modification of the processing apparatus which concerns on embodiment of this invention. It is a block diagram which shows another modification of the processing apparatus which concerns on embodiment of this invention. Figure 9 is a side view of a motorcycle with the treatment device shown in Figure 8; It is a block diagram which shows another modification of the processing apparatus which concerns on embodiment of this invention.

A processing apparatus, a motorcycle, and a processing method according to the present invention will be described below with reference to the drawings.

The configuration, operation, and the like described below are examples of the present invention, and the present invention is not limited to such configuration, operation, and the like.

For example, a motorcycle is exemplified below as a motorcycle. However, motorcycles are not limited to motorcycles. A motorcycle means a two-wheeled motor vehicle or a three-wheeled motor vehicle among saddle-riding vehicles on which a rider straddles. Motorcycles include motorcycles or tricycles that use an engine as a propulsion source, motorcycles or tricycles that use a motor as a propulsion source, and include, for example, motorcycles, scooters, and electric scooters.

Also, the same or similar descriptions are appropriately simplified or omitted below. Further, in each drawing, the same or similar members or portions are omitted from being given reference numerals or are given the same reference numerals. In addition, detailed structures are simplified or omitted as appropriate.

Embodiment.
A processing device according to an embodiment, a motorcycle equipped with the processing device, and a processing method according to an embodiment will be described below.

<Configuration of motorcycle and processing equipment>

FIG. 1 is a side view of a motorcycle according to an embodiment of the invention. The Z-axis shown in FIG. 1 is the vertical axis of the motorcycle 1 . The X-axis shown in FIG. 1 is the straight-traveling axis of the motorcycle 1 . 1 is an axis perpendicular to the vehicle body of the motorcycle 1 and perpendicular to the X and Z axes.

A motorcycle 1 comprises an inertial measurement sensor 2 and a processing device 10 . In other words, the motorcycle 1 is equipped with the inertial measurement sensor 2 and the processing device 10 .

The inertial measurement sensor 2 detects three-axis acceleration and three-axis (roll, pitch, yaw) angular velocities occurring in the motorcycle 1 . Specifically, the inertial measurement sensor 2 detects accelerations in, for example, the X-axis direction, the Y-axis direction, and the Z-axis direction. Further, for example, the inertial measurement sensor 2 detects an angular velocity about the X-axis as the roll angular velocity, an angular velocity about the Y-axis as the pitch angular velocity, and an angular velocity about the Z-axis as the yaw angular velocity. Note that the inertial measurement sensor 2 may detect other physical quantities that can be substantially converted into triaxial acceleration and triaxial angular velocity occurring in the motorcycle 1 . Alternatively, the inertial measurement sensor 2 may detect part of the triaxial acceleration and triaxial angular velocity.

Inertial measurement sensor 2 is used to control the behavior of motorcycle 1 . In other words, the behavior of the motorcycle 1 is controlled by a control device (not shown) based on the output of the inertial measurement sensor 2 . Conventionally, various methods have been proposed as specific methods for controlling the behavior of a motorcycle. A method of controlling the behavior of the motorcycle 1 by a control device (not shown) is not particularly limited, and various conventionally proposed methods can be adopted.

The processing device 10 determines whether the road surface is wet based on the output of the inertial measurement sensor 2 . For example, part or all of the processing device 10 is composed of a microcomputer, a microprocessor unit, or the like. Further, for example, part or all of the processing device 10 may be composed of an updatable device such as firmware, or may be a program module or the like executed by a command from a CPU or the like. For example, one processing device 10 may be provided, or a plurality of processing devices may be provided. Moreover, at least part of the processing device 10 may be integrated with at least part of the control device (not shown) described above. The processing device 10 can be configured, for example, as follows.

FIG. 2 is a block diagram showing a processing device according to an embodiment of the invention.
A processing device 10 according to the present embodiment includes an acquisition unit 11 and a determination unit 12 as functional units.

The acquisition unit 11 is a functional unit that acquires the running characteristics of the motorcycle 1 based on the output of the inertial measurement sensor 2 . A running characteristic is a vector whose axis is at least one of a physical quantity output from the inertial measurement sensor 2 (or a physical quantity converted from the physical quantity) and a Mahalanobis distance, which will be described later. In other words, the running characteristics can also be said to be the coordinates of a graph whose axis is at least one of the physical quantity output from the inertial measurement sensor 2 (or the physical quantity converted from the physical quantity) and the Mahalanobis distance described later. In the following description, a vector whose axis is at least one physical quantity output from the inertial measurement sensor 2 (or a physical quantity converted from the physical quantity) is referred to as running state information. Here, the physical quantity output from the inertial measurement sensor 2 (or the physical quantity converted from the physical quantity) includes three-axis acceleration, roll angular velocity, roll angle (integral value of roll angular velocity), yaw angular velocity, yaw angle (integrated value of yaw angular velocity), pitch angular velocity, and pitch angle (integrated value of pitch angular velocity). Note that, hereinafter, among these physical quantities, physical quantities in the roll direction such as roll angular velocity and roll angle may be collectively referred to as roll information. Further, hereinafter, among these physical quantities, physical quantities in the yaw direction such as yaw angular velocity and yaw angle may be collectively referred to as yaw information. For example, the acquisition unit 11 acquires the value of the physical quantity that is the axis of the running characteristic at a certain time. Thereby, the acquiring unit 11 can acquire the driving characteristics at a certain time.

The determination unit 12 is a functional unit that compares the driving characteristics acquired by the acquisition unit 11 with reference data and determines whether the road surface is wet. The determination unit 12 determines whether the road surface is wet, for example, as follows.

FIG. 3 and FIG. 4 are diagrams for explaining an example of a road surface wetness determination method performed by the determination unit of the processing device according to the embodiment of the present invention.

FIG. 3 shows, as the running characteristics of the motorcycle 1 acquired by the acquiring unit 11, the running characteristics that are vectors whose axis is the physical quantity x1, which is one of the physical quantities output from the inertial measurement sensor 2. . A black square shown in FIG. 3 indicates the running characteristic RQ of the motorcycle 1 at a certain time. Since the running characteristic RQ shown in FIG. 3 is a vector whose axis is the physical quantity output from the inertial measurement sensor 2, it can be said that it represents the running state information of the motorcycle 1 at a certain time. Here, FIG. 3 shows a reference sample group of vectors having the physical quantity x1 as an axis, out of the reference sample group of the running state information of the motorcycle 1 . A reference specimen group is a collection of a plurality of reference specimens. The reference sample is running state information of the motorcycle 1 acquired when it is known whether or not the road surface is wet. A small black circle shown in FIG. 3 is a reference sample when the road surface is not wet. Also, the black triangles shown in FIG. 3 are reference samples when the road surface is wet.

The behavior of the motorcycle 1 differs depending on whether the road surface is wet or not. That is, the physical quantity indicating the running state information of the motorcycle 1 differs depending on whether the road surface is wet or not. Therefore, the area Ad in which the reference specimen group exists when the road surface is not wet and the area Aw in which the reference specimen group exists when the road surface is wet are located at different positions. Note that the area Ad and the area Aw may partially overlap depending on the type of physical quantity.

Therefore, for example, the determining unit 12 can determine the wetness of the road surface using the reference sample group described above as reference data, in other words, using the area Ad and the area Aw as reference data. Specifically, it is assumed that the running characteristic RQ of the motorcycle 1 at a certain time is in the region Ad. In this case, the determining unit 12 can determine that the road surface is not wet at a certain time when the driving characteristics RQ are acquired. It is also assumed that the running characteristic RQ of motorcycle 1 at a certain time is in region Aw. In this case, the determining unit 12 can determine that the road surface is wet at a certain time when the driving characteristics RQ are acquired.

Further, for example, the reference data may include a boundary B that separates a reference sample group when the road surface is not wet and a reference sample group when the road surface is wet. In other words, the reference data may include a boundary B that separates the running characteristics of the motorcycle 1 when the road surface is not wet from the running characteristics of the motorcycle 1 when the road surface is wet. Then, the determination unit 12 may be configured to determine whether the road surface is wet based on the boundary B. Specifically, it is assumed that the running characteristic RQ of the motorcycle 1 at a certain time exists on the side of the running characteristic of the motorcycle 1 when the road surface is not wet with respect to the boundary B as a reference. In this case, the determining unit 12 can determine that the road surface is not wet at a certain time when the driving characteristics RQ are acquired. Further, it is assumed that the running characteristic RQ of motorcycle 1 at a certain time exists on the side of the running characteristic of motorcycle 1 when the road surface is wet with boundary B as a reference. In this case, the determining unit 12 can determine that the road surface is wet at a certain time when the driving characteristics RQ are acquired. Note that, as shown in FIG. 3, when the acquisition unit 11 acquires the running characteristic that is a vector having one physical quantity x1 as an axis, the boundary B becomes a boundary point.

FIG. 4 shows, as the running characteristics of the motorcycle 1 acquired by the acquiring unit 11, the running characteristics that are vectors having two physical quantities x1 and x2 out of the physical quantities output from the inertial measurement sensor 2 as axes. ing. A black square shown in FIG. 4 indicates the running characteristic RQ of the motorcycle 1 at a certain time. Since the running characteristic RQ shown in FIG. 4 is a vector whose axis is the physical quantity output from the inertial measurement sensor 2, it can be said that it represents the running state information of the motorcycle 1 at a certain time. FIG. 4 also shows a reference sample group of vectors having physical quantities x1 and x2 as axes. A small black circle shown in FIG. 4 is a reference sample when the road surface is not wet. Also, the black triangles shown in FIG. 4 are reference samples when the road surface is wet.

Even when the acquisition unit 11 acquires the running characteristics that are vectors with the two physical quantities x1 and x2 as the axes, the determining unit 12 determines the running characteristics acquired by the acquisition unit 11 and the reference data in the same manner as described above. can be compared to determine the wetness of the road surface. For example, the determination unit 12 can determine wetness of the road surface using the reference specimen group shown in FIG. 4 as reference data, in other words, using the area Ad and area Aw shown in FIG. 4 as reference data. Specifically, it is assumed that the running characteristic RQ of the motorcycle 1 at a certain time is in the region Ad. In this case, the determining unit 12 can determine that the road surface is not wet at a certain time when the driving characteristics RQ are acquired. It is also assumed that the running characteristic RQ of motorcycle 1 at a certain time is in region Aw. In this case, the determining unit 12 can determine that the road surface is wet at a certain time when the driving characteristics RQ are acquired.

Further, even when the acquisition unit 11 acquires the driving characteristics that are vectors with the two physical quantities x1 and x2 as the axes, the reference data includes a reference sample group when the road surface is not wet and a reference sample group when the road surface is wet. A boundary B may be set to separate the group of reference specimens. In other words, the reference data may include a boundary B that separates the running characteristics of the motorcycle 1 when the road surface is not wet from the running characteristics of the motorcycle 1 when the road surface is wet. Even when the acquisition unit 11 acquires the running characteristics that are vectors with the two physical quantities x1 and x2 as axes, the determination unit 12 can determine whether the road surface is wet based on the boundary B in the same manner as described above. can.

Specifically, it is assumed that the running characteristic RQ of the motorcycle 1 at a certain time exists on the side of the running characteristic of the motorcycle 1 when the road surface is not wet with respect to the boundary B as a reference. In this case, the determining unit 12 can determine that the road surface is not wet at a certain time when the driving characteristics RQ are acquired. Further, it is assumed that the running characteristic RQ of motorcycle 1 at a certain time exists on the side of the running characteristic of motorcycle 1 when the road surface is wet with boundary B as a reference. In this case, the determining unit 12 can determine that the road surface is wet at a certain time when the driving characteristics RQ are acquired. Note that, as shown in FIG. 4, when the acquisition unit 11 acquires the running characteristic that is a vector having two physical quantities x1 and x2 as axes, the boundary B is a boundary line. This boundary line may be a straight line or a line other than a straight line (curved line, polygonal line, etc.).

In FIGS. 3 and 4, the reference specimen group when the road surface is not wet and the reference specimen group when the road surface is wet do not overlap. However, even if the reference sample group when the road surface is not wet and the reference sample group when the road surface is wet overlap, a boundary B can be set in the reference data by a method such as a support vector machine.

3 and 4, the road surface wetness determination method by the determining unit 12 has been described by taking as an example the running characteristics, which are vectors having two or less physical quantities as axes. Not limited to this, the acquisition unit 11 may acquire driving characteristics that are vectors having three or more physical quantities as axes. Then, the determining unit 12 may determine whether the road surface is wet based on the driving characteristics, for example, as described above. As the number of physical quantities used to determine road surface wetness increases, the determination accuracy of road surface wetness by the determination unit 12 improves. On the other hand, the smaller the physical quantity used to determine whether the road surface is wet, the smaller the processing amount of the processing device 10, so the cost of the processing device 10 can be reduced.

Here, it is preferable that at least one axis of the running characteristic is physical quantity of at least one of roll information and yaw information. In other words, the acquisition unit 11 preferably acquires the running characteristics based on the roll information of the motorcycle 1 output from the inertial measurement sensor 2 . Moreover, it is preferable that the acquisition unit 11 acquires the running characteristics based on the yaw information of the motorcycle 1 output from the inertial measurement sensor 2 . There is likely to be a large difference in the turning behavior of the motorcycle 1 between when the road surface is wet and when it is not wet. Specifically, when the road surface is wet, the driver of motorcycle 1 suppresses the slippage of motorcycle 1 compared to when the road surface is not wet. The slope tends to be small. Therefore, the values of the roll information and the yaw information are likely to vary depending on whether the road surface is wet or not. Therefore, by acquiring the running characteristics based on at least one of the roll information and the yaw information of the motorcycle 1, the determination unit 12 can improve the accuracy of determining wetness of the road surface.

By the way, the acquisition unit 11 may acquire the distance to the reference sample group of the running state information of the motorcycle 1 output from the inertial measurement sensor 2, and acquire the running characteristics of the motorcycle 1 based on the distance. In other words, the distance between the running state information of the motorcycle 1 output from the inertial measurement sensor 2 and the reference sample group may be obtained, and the running characteristics of the motorcycle 1 may be obtained based on the distance. That is, the distance may be used as one of the axes of the running characteristics. For example, assume that the acquisition unit 11 acquires the distance between the running state information of the motorcycle 1 output from the inertial measurement sensor 2 and the reference sample group when the road surface is not wet. In this case, the greater the distance, the higher the possibility that the road surface is wet. Also, the smaller the distance, the higher the possibility that the road surface is not wet. Therefore, the distance can be used as one of the axes of the running characteristics. When obtaining the distance, the obtaining unit 11 may obtain the distance based on a stored arithmetic expression, or may use a table that associates the parameters in the arithmetic expression with the distance. may be asked for.

As the distance between the running state information of the motorcycle 1 output from the inertial measurement sensor 2 and the reference sample group, it is conceivable to use Euclidean distance, Mahalanobis distance, or the like. At this time, it is preferable to use the Mahalanobis distance as the distance between the running state information of the motorcycle 1 output from the inertial measurement sensor 2 and the reference sample group. This is for the following reasons, for example. In FIGS. 3 and 4, attention is paid to the reference sample group when the road surface is not wet or the reference sample group when the road surface is wet. In the reference sample group, each reference sample is not evenly distributed from the center of gravity of the reference sample group (or the average of each reference sample), but is widely distributed in one direction. In such a case, even if the distance between the running state information of the motorcycle 1 and the center of gravity of the reference sample group is the same, it may be located inside the reference sample group, or may be located outside the reference sample group. may be located in Therefore, depending on how the reference samples in the reference sample group are dispersed, the Euclidean distance may not be suitable as one of the axes of the running characteristics. On the other hand, the Mahalanobis distance indicates the distance from the reference specimen group, and increases as the distance from the reference specimen group increases. Therefore, it is preferable to use the Mahalanobis distance as the distance between the running state information of the motorcycle 1 output from the inertial measurement sensor 2 and the reference sample group.

Further, when the acquisition unit 11 acquires the running characteristics of the motorcycle 1 based on the Mahalanobis distance, the reference sample group used for acquiring the Mahalanobis distance is the reference sample group of the running state information of the motorcycle 1 when the road surface is not wet. A sample group is preferred. For example, as an example of using the determination result of the determination unit 12, it is possible to use the determination result of the determination unit 12 for controlling the behavior of the motorcycle 1. FIG. In such a case, the behavior of the motorcycle 1 is controlled such that when it is determined that the road surface is wet, the variation is gentler than when it is determined that the road surface is not wet. At this time, due to some influence, the running state information of the motorcycle 1 output from the inertial measurement sensor 2 is considered to be different from the reference sample group when the road surface is not wet and the reference sample group when the road surface is wet. assume to be. In such a case, if the acquisition unit 11 acquires the running characteristics of the motorcycle 1 based on the reference sample group of the running state information of the motorcycle 1 when the road surface is not wet, the determination unit 12 , it is determined that the road surface is wet. Therefore, the behavior of the motorcycle 1 is controlled so that the fluctuations in the behavior of the motorcycle 1 are moderated. Therefore, if the acquisition unit 11 acquires the running characteristics of the motorcycle 1 based on the reference sample group of the running state information of the motorcycle 1 when the road surface is not wet, the safety of the motorcycle 1 can be improved. improves.

FIG. 5 is a diagram for explaining a suitable period when the determining unit of the processing device according to the embodiment of the present invention determines whether the road surface is wet. Note that the horizontal axis of FIG. 5 represents time. The vertical axis in FIG. 5 is the vehicle speed of the motorcycle 1 . That is, FIG. 5 shows how the motorcycle 1 begins to decelerate from time T0.

When the road surface is wet, the driver of the motorcycle 1 tends to gradually decelerate the motorcycle 1 in order to suppress slipping and the like of the motorcycle 1 compared to when the road surface is not wet. Therefore, when the motorcycle 1 decelerates, there is likely to be a difference in behavior depending on whether the road surface is wet or not. That is, when the motorcycle 1 decelerates, the physical quantity output from the inertial measurement sensor 2 (or the physical quantity converted from the physical quantity) is likely to vary depending on whether the road surface is wet or not. For this reason, the timing at which the determination unit 12 determines whether the road surface is wet is not particularly limited, but the determination unit 12 determines whether the road surface is wet based on the output of the inertial measurement sensor 2 when the motorcycle 1 is decelerating. configuration is preferred. As a result, the determination accuracy of road surface wetness by the determination unit 12 is improved. For example, when the motorcycle 1 behaves as shown in FIG. 5, the determination unit 12 preferably determines whether the road surface is wet after time T0.

The configuration in which the determination unit 12 determines deceleration of the motorcycle 1 is not particularly limited. For example, the determination unit 12 determines whether the motorcycle 1 is braked, the throttle opening of the motorcycle 1 has decreased, or the vehicle speed of the motorcycle 1 has decreased. Deceleration can be determined. Also, the configuration for acquiring the vehicle speed of the motorcycle 1 by the determination unit 12 is not particularly limited. For example, the determination unit 12 is not limited to the configuration for acquiring the vehicle speed itself of the motorcycle 1, and acquires the vehicle speed based on other physical quantities (wheel speed, GPS position information, etc.) that can be converted into vehicle speed. You may

Further, when the vehicle speed of the motorcycle 1 is slow, the difference in the behavior of the motorcycle 1 between the wet road surface and the non-wet road surface becomes small. That is, when the vehicle speed of the motorcycle 1 is slow, the difference in the value of the physical quantity output from the inertial measurement sensor 2 (or the physical quantity converted from the physical quantity) is small between when the road surface is wet and when the road surface is not wet. Become. Therefore, it is preferable that the determination unit 12 determines whether the road surface is wet based on the output of the inertial measurement sensor 2 when the motorcycle 1 is at or above the specified speed. As a result, erroneous determination of wetness of the road surface by the determination unit 12 can be suppressed, and accuracy of determination of wetness of the road surface by the determination unit 12 is improved. For example, when the motorcycle 1 behaves as shown in FIG. It is preferable to judge Here, this effect is obtained not only when the judgment start timing of road surface wetness of the judging section 12 is when the motorcycle 1 decelerates.

Note that the configuration of the determination unit 12 for determining whether or not the motorcycle 1 is traveling at a speed equal to or higher than the specified speed is not particularly limited. For example, the determination unit 12 may determine whether or not the motorcycle 1 is traveling at or above a specified speed based on the vehicle speed of the motorcycle 1 or other physical quantity that can be substantially converted into vehicle speed. Further, for example, the determination unit 12 may determine whether or not the motorcycle 1 is traveling at a speed equal to or higher than a specified speed based on the elapsed time since the motorcycle 1 started decelerating.

<Operation of processing device>
The operation of the processing device 10 according to the embodiment will be described.

FIG. 6 is a diagram showing an example control flow of the operation of the processing device according to the embodiment of the present invention.
When the control disclosure condition is satisfied, the processing device 10 starts the control shown in FIG. 6 in step S1. The control start condition is, for example, when the motorcycle 1 starts decelerating. In this embodiment, the determination unit 12 determines whether or not the start condition is satisfied. Step S2 is an acquisition step. In step S<b>2 , the acquisition unit 11 of the processing device 10 acquires the running characteristics of the motorcycle 1 based on the output of the inertial measurement sensor 2 used for controlling the behavior of the motorcycle 1 . Note that the acquisition unit 11 may periodically repeat the operation of acquiring the running characteristics of the motorcycle 1 based on the output of the inertial measurement sensor 2 before the condition for starting control is met.

Step S3 after step S2 is a determination step. In step S3, the determination unit 12 of the processing device 10 compares the driving characteristics acquired in the acquisition step with the reference data to determine wetness of the road surface. Step S4 after step S3 is an end determination step. In step S4, the processing device 10 determines whether or not a control termination condition is met. The control end condition is, for example, when the motorcycle 1 becomes slower than the specified speed. In this embodiment, the determination unit 12 determines whether or not the end condition is satisfied. If the control end condition is met, the processing device 10 proceeds to step S5 and ends the control shown in FIG. On the other hand, if the control end condition is not satisfied, the processing device 10 repeats steps S2 to S4.

<Effect of processing equipment>
The processing device 10 is a processing device mounted on the motorcycle 1 . The processing device 10 includes an acquisition unit 11 and a determination unit 12 . The acquisition unit 11 acquires the running characteristics of the motorcycle 1 based on the output of the inertial measurement sensor 2 used for controlling the behavior of the motorcycle 1 . The determination unit 12 compares the driving characteristics acquired by the acquisition unit 11 with the reference data to determine whether the road surface is wet.

Conventional motorcycles have had to be equipped with raindrop sensors that directly detect rain in order to determine whether the road surface is wet. Therefore, conventional motorcycles that can determine whether the road surface is wet are expensive. On the other hand, the processing device 10 according to the present embodiment can determine wetness of the road surface based on the output of the inertial measurement sensor 2 . Here, conventionally, a motorcycle whose behavior is controlled has an inertial measurement sensor used for controlling the behavior of the motorcycle. Therefore, the cost of the motorcycle 1 can be reduced when changing the motorcycle 1 whose behavior is controlled to a motorcycle that can determine whether the road surface is wet.

<Modification>
FIG. 7 is a block diagram showing a modification of the processing device according to the embodiment of the invention.
A processing apparatus 10 shown in FIG. 7 includes a control unit 13 in addition to the configuration shown in FIG. The control unit 13 is a functional unit that uses the determination result of the determination unit 12 to control the behavior of the motorcycle 1 . The control unit 13 may be a part of the configuration of the above-described control device (not shown) that controls the behavior of the motorcycle 1 based on the output of the inertial measurement sensor 2, or may be separate from the configuration of the control device. may be configured.

The processing device 10 configured as shown in FIG. 7 can reflect whether the road surface is wet or not in controlling the behavior of the motorcycle 1 . For example, when it is determined that the road surface is wet, the control unit 13 controls the behavior of the motorcycle 1 so that the variation in behavior of the motorcycle 1 is gentler than when it is determined that the road surface is not wet. 1 behavior can be controlled. Specifically, for example, the control unit 13 can moderately control fluctuations in the behavior of the motorcycle 1 by controlling the torque, throttle opening, and the like of the motorcycle 1 . Therefore, by configuring the processing device 10 as shown in FIG. 7, the safety of the motorcycle 1 equipped with the processing device 10 is improved.

FIG. 8 is a block diagram showing another modification of the processing device according to the embodiment of the invention. 9 is a side view of a motorcycle equipped with the processing device shown in FIG. 8. FIG.
A motorcycle 1 shown in FIG. 9 includes a display device 3, which is an example of a notification device.

The processing device 10 shown in FIG. 8 includes a notification operation executing section 14 in addition to the configuration shown in FIG. The notification operation execution unit 14 is a functional unit that outputs a signal for informing the notification device of the determination result of the determination unit 12 . The specific content to be notified is, for example, whether the road surface is wet or not. As described above, the motorcycle 1 shown in FIG. 9 uses the display device 3 as a notification device. Therefore, in the motorcycle 1 shown in FIG. 9, the notification operation executing section 14 outputs a signal to cause the display device 3 to display the judgment result of the judging section 12 . As a result, the judgment result of the judging section 12 is displayed on the display device 3 .

Note that the notification device is not limited to the display device 3 . For example, a speaker or the like provided on the motorcycle 1 may be used as the notification device to notify the determination result of the determination section 12 by sound. In this case, the notification operation execution unit 14 outputs a notification signal that causes the notification device to emit a sound indicating the determination result of the determination unit 12 . Further, the notification device that receives the notification signal output from the notification operation executing section 14 is not limited to the configuration provided in the motorcycle 1 . Equipment associated with the motorcycle 1, such as a helmet and gloves worn by the driver of the motorcycle 1, may also be used. In other words, the notification operation executing section 14 may output a notification signal to equipment associated with the motorcycle 1, and the equipment may notify.

The processing device 10 configured as shown in FIG. 8 can make the driver of the motorcycle 1 recognize whether the road surface is wet or not. Therefore, by configuring the processing device 10 as shown in FIG. 8, the safety of the motorcycle 1 equipped with the processing device 10 is improved. Note that the processing device 10 shown in FIG. 8 may include the control unit 13 shown in FIG.

FIG. 10 is a block diagram showing still another modification of the processing device according to the embodiment of the invention.
A processing apparatus 10 shown in FIG. 10 includes a storage unit 15 in addition to the configuration shown in FIG. The storage unit 15 is a functional unit that stores the determination result of the determination unit 12 . By configuring the processing device 10 as shown in FIG. 10, the determination result of the determination unit 12 can be used for post-analysis of the driver's driving, skill determination, and the like. Therefore, by configuring the processing apparatus 10 as shown in FIG. 10, the convenience of the processing apparatus 10 is improved. Note that the processing device 10 shown in FIG. 10 may include the control unit 13 shown in FIG. 7, or may include the notification operation execution unit 14 shown in FIG.

Although the processing apparatus 10 according to the present embodiment has been described above, the processing apparatus according to the present invention is not limited to the description of the present embodiment, and only a part of the present embodiment is implemented. good too.

1 motorcycle, 2 inertial measurement sensor, 3 display device, 10 processing device, 11 acquisition unit, 12 determination unit, 13 control unit, 14 notification operation execution unit, 15 storage unit.

Claims (13)

A processing device (10) mounted on a motorcycle (1),
an acquisition unit (11) for acquiring the running characteristics of the motorcycle (1) based on the output of an inertial measurement sensor (2) used for controlling the behavior of the motorcycle (1);
a determination unit (12) that compares the driving characteristics acquired by the acquisition unit (11) with reference data and determines wetness of the road surface;
A processing device (10) comprising: The processing device according to claim 1, wherein the acquisition unit (11) acquires the running characteristics based on the roll information of the motorcycle (1) output from the inertial measurement sensor (2). 10). The acquisition unit (11) is configured to acquire the running characteristic based on the yaw information of the motorcycle (1) output from the inertial measurement sensor (2). processing unit (10). The acquisition unit (11) acquires a Mahalanobis distance with respect to a reference sample group of running state information of the motorcycle (1) output from the inertial measurement sensor (2), and calculates the running characteristics based on the Mahalanobis distance. A processing device (10) according to any one of claims 1 to 3, configured to acquire. The processing device (10) according to claim 4, wherein the reference sample group is a reference sample group of the driving state information when the road surface is not wet. A boundary (B) is set in the reference data to separate the running characteristics when the road surface is not wet and the running characteristics when the road surface is wet,
The processing device (10) according to any one of claims 1 to 5, wherein the determination unit (12) determines wetness of the road surface based on the boundary (B). The judging section (12) judges whether the road surface is wet based on the output of the inertial measurement sensor (2) when the motorcycle (1) is decelerating. A processor (10) according to any one of Claims 1 to 3. The determination unit (12) determines whether the road surface is wet based on the output of the inertial measurement sensor (2) when the motorcycle (1) is at or above a specified speed (V1). A processing unit (10) according to any one of claims 1 to 7. The processing device according to any one of claims 1 to 8, further comprising a control unit (13) that uses the determination result of the determination unit (12) to control the behavior of the motorcycle (1). 10). The processing device according to any one of claims 1 to 9, further comprising a notification operation execution unit (14) for outputting a signal for notifying a notification device (3) of the determination result of the determination unit (12). (10). The processing device (10) according to any one of claims 1 to 10, further comprising a storage section (15) for storing determination results of the determination section (12). A motorcycle (1) comprising a treatment device (10) according to any one of claims 1 to 11. A treatment method for use in a motorcycle (1), comprising:
an acquisition step (S2) for acquiring the running characteristics of the motorcycle (1) based on the output of an inertial measurement sensor (2) used for controlling the behavior of the motorcycle (1);
a determination step (S3) for determining wetness of the road surface by comparing the driving characteristics acquired in the acquisition step (S2) with reference data;
processing method.

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